Rapid identification of microbial contaminants in pharmaceutical products using a PCA/LDA-based FTIR-ATR method

Brito, Natália Monte Rubio de; Lourenço, Felipe Rebello

doi:10.1590/s2175-97902020000318899

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…The strain used in this experiment was Escherichia coli (ATCC8739) [ 24 , 25 , 26 , 27 ], which was purchased from Guangdong Huankai Microbiology Technology Co Ltd. The Tryptic Soy Broth (TSB) was used as the liquid medium [ 28 ], the Plate Count Agar (PCA) was used as the solid medium [ 29 ], and the 0.9% sterile saline was used as the dilution solution [ 29 , 30 ].…”

Section: Materials and Methodsmentioning

confidence: 99%

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

Zhang

Zhou²,

Cao³

et al. 2022

Biology

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Bacterial colony counting is a time consuming but important task for many fields, such as food quality testing and pathogen detection, which own the high demand for accurate on-site testing. However, bacterial colonies are often overlapped, adherent with each other, and difficult to precisely process by traditional algorithms. The development of deep learning has brought new possibilities for bacterial colony counting, but deep learning networks usually require a large amount of training data and highly configured test equipment. The culture and annotation time of bacteria are costly, and professional deep learning workstations are too expensive and large to meet portable requirements. To solve these problems, we propose a lightweight improved YOLOv3 network based on the few-shot learning strategy, which is able to accomplish high detection accuracy with only five raw images and be deployed on a low-cost edge device. Compared with the traditional methods, our method improved the average accuracy from 64.3% to 97.4% and decreased the False Negative Rate from 32.1% to 1.5%. Our method could greatly improve the detection accuracy, realize the portability for on-site testing, and significantly save the cost of data collection and annotation over 80%, which brings more potential for bacterial colony counting.

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Section: Materials and Methodsmentioning

confidence: 99%

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

Zhang

Zhou²,

Cao³

et al. 2022

Biology

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Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Kassem,

Abbas,

Coutinho

et al. 2023

Front. Microbiol.

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Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

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Rapid identification of microbial contaminants in pharmaceutical products using a PCA/LDA-based FTIR-ATR method

Cited by 2 publications

References 23 publications

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

A New Few-Shot Learning Method of Bacterial Colony Counting Based on the Edge Computing Device

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

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